{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["15(1)"],"submitter":["Luo Y"],"pubmed_abstract":["Liquid-liquid phase separation (LLPS) has been linked to the initiation and progression of cancers. This study aimed to investigate the LLPS-related molecular features and develop a prognostic signature for hepatocellular carcinoma (HCC). Single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data were obtained from open-source repositories. The Seurat package was used for processing and analyzing scRNA-seq data. LLPS-related genes (LLPSRGs) were identified by integrating scRNA-seq and bulk RNA-seq data. Univariate Cox and LASSO regression analyses were employed to construct an LLPS-related prognostic risk model. A predictive nomogram was also developed based on the risk score and clinicopathologic features. Additionally, correlations between clinicopathological features, biological funct"],"journal":["Scientific reports"],"pagination":["36805"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12541017"],"repository":["biostudies-literature"],"pubmed_title":["Integration of single-cell and bulk RNA sequencing data to identify liquid-liquid phase separation-related prognostic biomarkers in hepatocellular carcinoma."],"pmcid":["PMC12541017"],"pubmed_authors":["Luo Y","Wang X"],"additional_accession":[]},"is_claimable":false,"name":"Integration of single-cell and bulk RNA sequencing data to identify liquid-liquid phase separation-related prognostic biomarkers in hepatocellular carcinoma.","description":"Liquid-liquid phase separation (LLPS) has been linked to the initiation and progression of cancers. This study aimed to investigate the LLPS-related molecular features and develop a prognostic signature for hepatocellular carcinoma (HCC). Single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data were obtained from open-source repositories. The Seurat package was used for processing and analyzing scRNA-seq data. LLPS-related genes (LLPSRGs) were identified by integrating scRNA-seq and bulk RNA-seq data. Univariate Cox and LASSO regression analyses were employed to construct an LLPS-related prognostic risk model. A predictive nomogram was also developed based on the risk score and clinicopathologic features. Additionally, correlations between clinicopathological features, biological funct","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Oct","modification":"2026-06-04T15:19:35.706Z","creation":"2026-05-10T03:12:20.604Z"},"accession":"S-EPMC12541017","cross_references":{"pubmed":["41120586"],"doi":["10.1038/s41598-025-20691-6"]}}